4.8 Review

On state-of-charge determination for lithium-ion batteries

Journal

JOURNAL OF POWER SOURCES
Volume 348, Issue -, Pages 281-301

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2017.03.001

Keywords

Li-ion battery; State of charge (SOC); Calibration; Regression; Multi-physics battery model; Statistical accuracy

Funding

  1. U.S. Department of Energy [DE-AC07-05ID14517]
  2. Foundation of State Key Laboratory of Automotive Safety and Energy at Tsinghua University, Beijing, China [KF14041, KF16052]
  3. National Natural Science Foundation of China [51577104, 51377097]
  4. United States Government

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Accurate estimation of state-of-charge (SOC) of a battery through its life remains challenging in battery research. Although improved precisions continue to be reported at times, almost all are based on regression methods empirically, while the accuracy is often not properly addressed. Here, a comprehensive review is set to address such issues, from fundamental principles that are supposed to define SOC to methodologies to estimate SOC for practical use. It covers topics from calibration, regression (including modeling methods) to validation in terms of precision and accuracy. At the end, we intend to answer the following questions: 1) can SOC estimation be self-adaptive without bias? 2) Why Ahcounting is a necessity in almost all battery-model-assisted regression methods? 3) How to establish a consistent framework of coupling in multi-physics battery models? 4) To assess the accuracy in SOC estimation, statistical methods should be employed to analyze factors that contribute to the uncertainty. We hope, through this proper discussion of the principles, accurate SOC estimation can be widely achieved. Published by Elsevier B.V.

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